Online Master of Science in Computer Science (MSCS)
Computer Science
Program Overview
The University of Tennessee, Knoxville’s online Master’s in Computer Science is designed for students and working professionals who want advanced technical training in computer science. With coursework in deep learning, software engineering, artificial intelligence, and security, the program helps students build specialized skills for today’s evolving technology landscape.
Students can complete the online MSCS in 10 to 24 months, with courses offered year-round. The program is designed to fit busy schedules while providing access to faculty with leadership and research experience across government, science, and industry. You’ll learn from experts whose experience includes:
- White House Office of Science and Technology Policy leadership
- National Science Foundation research
- Award-winning scientific and technical contributions
Build advanced technical skills for high-growth computer science roles. Earn your Master of Science in Computer Science from a top-ranked public engineering school—fully online and on your schedule.
Why Choose the Online MSCS Program?
The online MSCS program is designed for students with experience in computer science or a related field who want to deepen their technical expertise and prepare for advanced roles. Through focused coursework, students strengthen their problem-solving skills and gain practical knowledge in high-demand areas such as:
- Data Engineering
- Artificial Intelligence
- Software Security
- Cyber-Physical Systems Security
- Software Engineering
- Cloud and Web Computing
Unlike a general graduate degree, the online MS in Computer Science includes three required concentration options aligned with current industry needs:
- Artificial Intelligence and Machine Learning
- Cybersecurity
- Software Engineering
With input from faculty involved in national AI and software policy, as well as program design leadership associated with award-winning computer science research, the curriculum is designed to reflect both academic rigor and workforce relevance.
Flexible Admission Pathways
The online MSCS offers a flexible pathway for applicants who may not have a traditional computer science background. Eligible students can begin through the Spin-Up Pathway, which includes 1 to 3 foundational courses that help build the programming and computer science knowledge needed for success in the program.
Spin-Up Pathway Courses:
- COSC 103: Introduction to Computer Science
- COSC 203: Data Structures
- COSC 230: Computer Organization
Admission Requirements
- Bachelor’s degree from an accredited institution
- Minimum 3.0 cumulative undergraduate GPA
- For applicants with a GPA between 2.7 and 3.0, possible consideration through an exception process
- 3.3 cumulative GPA for international students
- Copies of official transcripts from all institutions attended, undergrad and grad (official transcripts upon admission)
- Resume
- Personal statement
- $60 application fee
Preferred Qualifications
Applicants should have coursework or relevant work experience in:
- Programming (Java, C, C++, and/or Python)
- Data structures and algorithms
- Computer architecture
- Systems programming
- Calculus (at least 1 semester)
- Linear algebra
- Discrete mathematics
- For relevant work experience, we request three letters of recommendation from individuals who can attest to your CS acumen. We also request that you add your competency in each of the items above to an updated resume or CV.
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Program Concentrations
The following three concentrations provide students with the specialized skills needed to be competitive leaders in the field:
Cybersecurity
The Cybersecurity concentration prepares you to defend systems and break down threats at the deepest level, whether you’re new to the field or ready for advanced work. You’ll master low-level programming, software security, and both asymmetric and symmetric cryptography while learning to spot computer architecture vulnerabilities, reverse engineer code, and run penetration tests to find weaknesses before attackers do. Through hands-on practice in defensive programming, you’ll build secure software and gain skills that connect directly to today’s job market. Graduates are ready for careers such as penetration testers, computer hardware engineers, network security engineers, or cipher mathematicians.
Artificial Intelligence and Machine Learning
The Artificial Intelligence and Machine Learning concentration equips you with the skills to work at the forefront of modern computing — no prior AI experience required. You’ll explore machine learning, large language models, deep neural networks, large data engineering, reinforcement learning, and digital fingerprinting and forensics, all on a flexible online schedule built for working adults. Graduates leave ready to pursue roles such as data scientists, data engineers, high-performance computing scientists, or prompt engineers.
Software Engineering
The Software Engineering concentration prepares you to design, build, and optimize the software that powers modern applications, whether you’re new to coding or ready to specialize. You’ll learn front-end web and graphic interface design, back-end and database engineering, scripting languages, and how to create tools for specific use cases like game development. Through hands-on study of software complexity (Big-O and Big-Omega), software optimization, database optimization, and group development workflows, you’ll gain real-world skills in cloud and web engineering that connect directly to today’s job market. Graduates are ready for careers such as software engineers, front-end developers, back-end developers, or library and API developers.
Featured Courses
Theoretical and practical aspects of machine learning techniques related to pattern recognition. Statistical methods studied include Bayesian and linear classifiers, support vector machines, neural networks, and unsupervised learning. Syntactic methods include grammatical inference, string matching, and Markov chains. Ensemble methods include random forests, adaptive boosting, and classifier fusion.
Theoretical and applied aspects of artificial intelligence. Course topics include problem solving and search, knowledge representation and reasoning, decision-making under uncertainty, machine learning, and multi-agent systems.
An in-depth introduction to software security. The focus is on identifying vulnerabilities in software, exploiting vulnerabilities in software, and software development best practices for avoiding vulnerabilities during the design, implementation, testing, and deployment of software. Coursework involves hands-on experience exploiting software vulnerabilities to increase understanding, awareness, and appreciation of software vulnerabilities.
Advanced coverage of software processes and technologies that can be used on large projects to help design, manage, maintain, and test software.
